Radio frequency (RF) spectrum is a scarce resource. In a cellular or personal communications systems environment, an increasing number of users need to be simultaneously serviced while also attempting to avoid interference among such users. One way to increase the number of simultaneous users on a given frequency band is code division multiple access (CDMA). CDMA refers to a form of multiplexing which allows numerous signals to occupy a single transmission channel thereby optimizing the use of available bandwidth. This technology is generally used in ultra-high-frequency (UHF) cellular telephone systems in the 800-MHz and 1.9-GHz bands.
CDMA is generally a complex, medium access control layer, which utilizes communications and signal processing schemes such as analog-to-digital conversion (ADC) and spread spectrum technology. Audio signals are digitized and processed by a modulator. In a frequency hopped system, the modulated signal is transmitted over a finite set of carrier frequencies with a sequence known a priori to a transmitter and a receiver. The CDMA receiver is reprogrammed to receive signals that are time and frequency aligned with those of the transmitter. This technique generally ensures that communications can be established over a link that is robust in a jamming environment.
In multi-code (MC) CDMA radio telephone systems, several CDMA signals associated with a single user may be sent between two stations in order to provide the user with a higher data rate. In such systems, each CDMA signal associated with a single user is spread using direct sequence (DS) spreading orthogonal codes such as Walsh codes. The spread signals are then scrambled using pseudo-noise (PN) sequence prior to transmission. As such, CDMA may be referred to more generally as DSPN. However, transmission quality of CDMA signals in such systems typically degrades when the signals travel over more than one path between the transmitter and the receiver. This is because such “multi-path propagation” causes co-channel interference between the transmitted CDMA signals. Multiuser communication systems that employ CDMA exhibit a limit on the number of users that can simultaneously communicate over a channel and maintain a specified level of performance per user. This limitation is caused by user interference dominance over additive thermal noise.
The CDMA codes are generated by functions, such as Walsh functions, which are mathematically orthogonal in higher dimensional space. Thus, any two Walsh functions are orthogonal to each other, and signals encoded with two separate Walsh functions should generally cause no mutual interference when they are time aligned. However, because multiple signals often are not time aligned, complete orthogonality is usually not achieved in practice. As a result, interference between otherwise orthogonal signals occurs. This is known as multiple access interference (MAI).
Rigorous analysis of multiple signal interference space may be further complicated by co-channel interference from signals having analytic and bandpass properties that are unknown. Separation of co-channel and adjacent channel interference in a mobile environment may be further complicated by fading and Doppler effects. Many current research efforts at addressing co-channel interference make a number of simplifying assumptions such as identical carriers, perfect carrier recovery, identical modulation domains, known data rates and bandwidths, isolated signals (e.g., for classification), non-ambiguous signal distributions, and stationary non-mobile conditions.
The separation of independent sources from an array of sensors is a classic and difficult problem in signal processing. Generally, the signal sources as well as their mixture characteristics are unknown. Without knowledge of the signal sources, other than a general assumption that the sources are independent, the signal processing is commonly known in the art as the blind separation of sources (BSS). The separation is “blind” because nothing is assumed about the independent source signals or about the mixing process. BSS techniques rely only on source signal independence and non-Gaussianity assumptions. BSS is a system in which the output of an independent mixture of blind sources and channels is observed and the input signals are recovered based on observations only.
A typical example of the blind separation of source signals is where the source signals are sounds generated by two independent sources, such as two (or more) separate speakers. An equal number of microphones (two in this example) are used to produce mixed signals, each composed as a weighted sum of the source signals. Each of the source signals is delayed and attenuated by some unknown amount during passage from the speaker to a microphone, where the source signals are mixed with delayed and attenuated components of other source signals. Multi-path signals, generated by multiple reflections of the source signals, may be further mixed with direct source signals. This is generally known as a “cocktail party” problem, since a person generally wishes to listen to a single sound source while filtering out other interfering sources, including multi-path signals.
In the cellular telecommunications art, for example, a receiver must eliminate interfering signals from neighboring cells or the same cell to avoid unacceptable levels of interference. Generally, a static linear signal mixing model has been used and applied to separation of multiple signals. A common assumption is made that the statistical properties of the signal and the channel remain stationary. However, in mobile communications, the signals are subject to fading. Usually there is no direct line of sight from the transmitter to the receiver, only multiple reflected and diffracted signal components reach the receiver. For example, obstacles such as buildings interfere with signal path and create reflections. When either the receiver or the transmitter is moving, such as in an urban environment, building reflections are changing very rapidly.
A signal classifier is a device that analyzes an input signal to determine a signal class of a plurality of signal classes to which the signal belongs. Signal classifiers have been used in communications systems to classify signals received from communications channel to determine how to properly process the signals. For example, a receiver generally needs to know the type of modulation present in a received signal to properly demodulate the signal. A signal classifier can be used to determine the modulation types so that a proper demodulation method can be selected.
In general, all signal classifiers examine signal feature differences to discriminate between signal classes. A cluttered, interference-laden environment tends to reduce the possible resolution between signal classes, resulting in a situation where similar signal classes are difficult to distinguish. For this reason, many conventional signal classifiers use “signal-specific” procedures and signal processing steps that preclude addition or deletion of signals-of-interest.
In view of the foregoing, it is desirable to provide co-channel interference separation that is effective for the more general cases wherein: modulations are not known a priori; signals are asynchronous; data rates, bandwidths, and carrier frequencies are unknown; and, the signal environment can include any combination of modulation domains. In addition, it would be desirable to provide spread spectrum communication having interference mitigation using co-channel interference separation that is effective in the aforementioned more general cases. Furthermore, additional desirable features provided by the invention will become apparent to one skilled in the art from the drawings, foregoing background, following detailed description, and appended claims.